Scanners, that is devices that can capture an image and convert it into a unique set of electrical signals are well known. Similarly 3-dimensional (3D) scanning systems are known that can image an object to obtain 3D surface representations of the object. Fields of application of 3D scanning systems are varied and, for example, include medical imaging, reverse engineering, computer vision, and video and film production. By object it is meant herein any physical entity such as a real object, a hidden object located below a surface, but viewable using certain kinds of radiation or a physical system such as a fluid flow that is not at first sight within the classical meaning of the term object.
The goal of structured light techniques is to measure the shape of three dimensional objects using automatic non-contact techniques. Early systems used a single stripe or spot of laser light to measure a small part of the object in each scan. Now the availability of controlled light output from LCD projectors allows the projection of a more complex pattern of light to increase the area measured in a single instantaneous scan.
(1) Single Stripe Systems
The classic single stripe scanning system is described in the following paper: J.-A. Beraldin, M. Rioux, F. Blais, G. Godin, R. Baribeau, (1992) Model-based calibration of a range camera, proceedings of the 11th International Conference on Pattern Recognition: 163-167. The Hague, The Netherlands. Aug. 30-Sep. 3, 1992, [Ber92a]. This system provides the profile of one “slice” through the target object. In order to build a model of the complete surface a number of spatially related profiles must be scanned. To achieve this a sequence of scans is captured. For each scan, the target object is moved in relation to the scanner, or the projected stripe moves in relation to the object, the movement being controlled to the same resolution as required by the scanning system. As will be understood by those skilled in the art such a single stripe system may require an accuracy of 1:20000.
(2) Multi-Stripe Systems
To avoid the need for accurate mechanisms and in order to speed up the acquisition process, a number of stripes can be projected at or substantially at the same time and captured as a sequence of stripes in a single frame. Unlike with the single stripe systems an accurate rotation estimate is not required and such systems offer free-form imaging by which it is meant imaging without the restriction of using a mechanical rotation device or a mechanical rotation indexing system.
3D multi-stripe scanning apparatus and methods are known for determining the order of a sequence of stripes captured in an uncoded structured light scanning system, i.e. where all the stripes are projected with uniform colour, width and spacing. A single bitmap image shows a pattern of vertical stripes from a projected source. If the target object is a planar surface then these stripes are uniformly spread over the surface in an intuitive manner. However these vertical stripes are deformed by the surfaces of more complex target objects, such as, for example, a target object comprising a physical model of a human head where in particular heavier distortion occurs around the nasal area. If a correspondence can be determined between the projected stripes and those captured in the bitmap, a spatial measurement of the surface can be derived using standard range-finding methods.
However, it is frequently difficult to determine which captured stripe corresponds to which projected stripe, when we attempt to index the captured sequence in the same order as the projected sequence. We call this the stripe indexing problem. For this reason methods have been devised to uniquely mark each stripe:
(1) by colour as described in the paper: C. Rocchini, P. Cignoni, C. Montani, P. Pingi and R. Scopigno, (2001) A low cost 3D scanner based on structured light, Computer Graphics Forum (Eurographics 2001 Conference Proc.), vol. 20 (3), 2001, pp. 299-308, Manchester, 4-7 Sep. 2001, [Roc01a];
(2) by stripe width as described in the paper: Raymond C. Daley and Laurence G. Hassebrook, (1998) Channel capacity model of binary encoded structured light-stripe illumination, in Applied Optics, Vol. 37, No 17, 10 Jun. 1998, [Dal98a]; and
(3) by a combination of both as described in the paper: Li Zhang, Brian Curless and Stephen M. Seitz, (2002) Rapid Shape Acquisition Using Color Structured Light and Multi-pass Dynamic Programming, 1st International Symposium on 3D data processing, visualization and transmission, Padova, Italy, Jun. 19-22, 2002, [Zha02a].
These and other works highlight the disadvantages of coded structured light: with colour indexing there may be weak or ambiguous reflections from surfaces of a particular colour, and with stripe width variations the resolution is less than for a uniform narrow stripe. This last problem can be addressed by projecting and capturing a succession of overlapping patterns of differing width as disclosed in the paper: Olaf Hall-Holt and Szymon Rusinkiewicz, (2001) Stripe Boundary Codes for Real-Time Structured-Light Range Scanning of Moving Objects, proceedings of the Eighth International Conference on Computer Vision (ICCV 2001), July 2001, [Hal01a]. However this means that it is not possible to measure the surface in a single frame. Single frame or “one-shot” capture is desirable because it speeds up the acquisition process, and leads to the possibility of capturing moving surfaces.
Moreover, because of the limits of any colour coding scheme, ambiguities will still exist; and stripe width coding is likely to increase the difficulty of interpreting shape correctly, such as when occlusions occur.
In summary, existing prior art methods are thus known which uniquely encode each stripe, such as by stripe colour or by stripe width, in order to avoid ambiguous stripe identification. However, colour coding suffers due to uneven colour reflection which is caused by the colour of the physical entity being imaged interfering with the colour coded stripes. A major problem with a variable width coded approach is that it reduces the measured resolution of the physical entity being imaged. In view of the problems with the prior art methods there is therefore a need to improve structured light scanning systems. Furthermore many other imaging methodologies using radiations other than structured light experience similar or related problems. Thus there is also a need to overcome such problems in various imaging methodologies that use radiations other than visible light.